Data Scientist at a educational organization with 5,001-10,000 employees
Real User
Top 10
Dec 12, 2025
I developed a chatbot with text summarization and question answering capabilities. I need to summarize multiple PDFs, and I have a database in Google Cloud Storage where I perform keyword matching with Elastic Search using exact keyword matching. I have different clients, but I use Elastic Cloud (Elasticsearch Service) for one specific client. For that one job, Elastic Cloud (Elasticsearch Service) is the main tool because I am using an Elastic Search strategy instead of a vector database.
We use Elastic Cloud (Elasticsearch Service), Kibana, Enterprise Search, and on-premise as in a cloud environment within our Bosch environment, and we have different customers using the search, ML, and other services. One of our customers uses Elastic Cloud (Elasticsearch Service) Agents out of the box when their server is installed, and this captures the metrics from the different servers within their environment, giving a unified Kibana view in the form of dashboards and helping us to understand the different key metrics which are relevant for them. They also use Elastic Cloud (Elasticsearch Service) for their search and indexing operations, and they also use agents and Fleet as different integration options, and finally, they also use the MLOps for their Elastic Cloud (Elasticsearch Service) ML for their AIOps purposes. We've got close to about 50-plus customers and we've got three huge clusters of Elastic Cloud (Elasticsearch Service) on three different environments, and customers are happy.
VP Engineering Services & Sercurity at Jitterbit, Inc
Real User
Top 10
Sep 29, 2025
My main use case for Elastic Cloud (Elasticsearch Service) is to capture logs from our various systems. For our cloud service, we have various Elastic agents that ship logs into a central location. We have it all aggregated in our Elastic Cloud. From there, we use the logs for troubleshooting, creating alerts, look for specific patterns, understanding our service a little bit better, and aggregating all that data in one place.
Learn what your peers think about Elastic Cloud (Elasticsearch Service). Get advice and tips from experienced pros sharing their opinions. Updated: May 2026.
Elastic Cloud (Elasticsearch Service) provides a managed platform for Elasticsearch, offering flexibility and scalability to handle search, logging, and analytics use cases efficiently, enhancing data-driven decision-making processes.As a managed service, Elastic Cloud (Elasticsearch Service) simplifies running and scaling Elasticsearch by automating setup and management tasks, reducing the overhead related to infrastructure maintenance. It supports a variety of use cases such as real-time...
I developed a chatbot with text summarization and question answering capabilities. I need to summarize multiple PDFs, and I have a database in Google Cloud Storage where I perform keyword matching with Elastic Search using exact keyword matching. I have different clients, but I use Elastic Cloud (Elasticsearch Service) for one specific client. For that one job, Elastic Cloud (Elasticsearch Service) is the main tool because I am using an Elastic Search strategy instead of a vector database.
We use Elastic Cloud (Elasticsearch Service), Kibana, Enterprise Search, and on-premise as in a cloud environment within our Bosch environment, and we have different customers using the search, ML, and other services. One of our customers uses Elastic Cloud (Elasticsearch Service) Agents out of the box when their server is installed, and this captures the metrics from the different servers within their environment, giving a unified Kibana view in the form of dashboards and helping us to understand the different key metrics which are relevant for them. They also use Elastic Cloud (Elasticsearch Service) for their search and indexing operations, and they also use agents and Fleet as different integration options, and finally, they also use the MLOps for their Elastic Cloud (Elasticsearch Service) ML for their AIOps purposes. We've got close to about 50-plus customers and we've got three huge clusters of Elastic Cloud (Elasticsearch Service) on three different environments, and customers are happy.
My main use case for Elastic Cloud (Elasticsearch Service) is to capture logs from our various systems. For our cloud service, we have various Elastic agents that ship logs into a central location. We have it all aggregated in our Elastic Cloud. From there, we use the logs for troubleshooting, creating alerts, look for specific patterns, understanding our service a little bit better, and aggregating all that data in one place.